Supeerstar's questions at Yahoo Answers regarding optimizing quadratic functions

In summary, the maximum possible area of the rectangle constructed with one vertex at the origin and another on the given line is 3 square units. The minimum value of 3x^2+7x-2 if -3\le x \le 0 is -\frac{73}{12} and the maximum value if 0\le x \le 3 is 46.
  • #1
MarkFL
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Here are the questions:

Help with solving these quadratic worded problems?


1) A rectangle is constructed so that one vertex is at the origin, and another vertex is on the graph of y=3 - 2x/3 where x >0 and y>0 and adjacent sides are on the axes. what is the maximum possible area of the rectangle?

2) What is the minimum value of 3x^2 +7x -2 if -3 ≤ x ≤ 0 ?

3) What is the maximum value of 3x^2 + 7x - 2 if 0 ≤ x ≤ 3?

I have posted a link there to this topic so the OP can see my work.
 
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  • #2
Hello supeerstar,

1.) Let's look at a plot of the given line and a rectangle constructed as instructed:

View attachment 1525

We see the area of the rectangle is:

\(\displaystyle A(x,y)=xy\)

We also see that we require \(\displaystyle 0\le x\le\frac{9}{2}\).

Since \(\displaystyle y=3-\frac{2x}{3}\) we may write:

\(\displaystyle A(x)=x\left(3-\frac{2x}{3} \right)=-\frac{2}{3}x^2+3x\)

Observing this is a parabola opening downwards, we know the maximum must occur on the axis of symmetry, given by:

\(\displaystyle x=-\frac{2}{2\left(-\frac{2}{3} \right)}=\frac{3}{2}\)

And so we find:

\(\displaystyle A_{\max}=A\left(\frac{3}{2} \right)=3\)

And so the maximum area of the rectangle is 3 square units.

For problems 2.) and 3.), let:

\(\displaystyle f(x)=3x^2+7x-2\)

We find the axis of symmetry for the given quadratic is:

\(\displaystyle x=-\frac{7}{2(3)}=-\frac{7}{6}\)

Since this is a quadratic opening upwards, we know the global minimum is:

\(\displaystyle f_{\min}=f\left(-\frac{7}{6} \right)=-\frac{73}{12}\)

For any interval wholly to the right of the axis of symmetry, we know the maximum value of the function is at the right end-point. Hence:

2.) \(\displaystyle f_{\min}=-\frac{73}{12}\)

3.) \(\displaystyle f_{\max}=f(3)=46\)
 

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FAQ: Supeerstar's questions at Yahoo Answers regarding optimizing quadratic functions

1. What is a quadratic function?

A quadratic function is a mathematical expression that contains a variable raised to the second power. It is written in the form of y = ax^2 + bx + c, where a, b, and c are constants and x is the variable. It is a polynomial function and its graph forms a parabola.

2. How do you optimize a quadratic function?

To optimize a quadratic function, you need to find the vertex, which is the highest or lowest point on the parabola depending on the direction it opens. This can be done by using the formula x = -b/2a to find the x-coordinate of the vertex, and then substituting this value into the function to find the corresponding y-coordinate. The vertex represents the optimal solution for the function.

3. What does it mean to maximize or minimize a quadratic function?

Maximizing a quadratic function means finding the highest point on the parabola, which is also known as the maximum value. Minimizing a quadratic function means finding the lowest point on the parabola, which is also known as the minimum value. These points represent the maximum or minimum possible output values for the function.

4. Can a quadratic function have more than one optimal solution?

Yes, it is possible for a quadratic function to have more than one optimal solution. This can occur when the parabola intersects the x-axis at two points, resulting in two x-values that produce the same optimal y-value. This is known as a double root or a repeated root.

5. How is a quadratic function used in real life?

Quadratic functions have many real-life applications, such as in physics, engineering, and economics. They can be used to model motion, such as the trajectory of a thrown object, or the growth and decline of populations. In economics, they can be used to determine the maximum profit or minimum cost for a given situation. They are also used in optimization problems in mathematics and computer science.

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